ovcTCGA: Function to compute the prediction scores and risk classifications for the ovarian cancer TCGA signature

Description

This function computes signature scores and risk classifications from gene expression values following the algorithm developed by the TCGA consortium for ovarian cancer.

Usage

ovcTCGA(data, annot, 
gmap = c("entrezgene", "ensembl_gene_id", "hgnc_symbol", "unigene"), 
do.mapping = FALSE, verbose = FALSE)

Arguments

data

Matrix of gene expressions with samples in rows and probes in columns, dimnames being properly defined.

annot

Matrix of annotations with one column named as gmap, dimnames being properly defined.

gmap

character string containing the biomaRt attribute to use for mapping if do.mapping=TRUE

do.mapping

TRUE if the mapping through Entrez Gene ids must be performed (in case of ambiguities, the most variant probe is kept for each gene), FALSE otherwise.

verbose

TRUE to print informative messages, FALSE otherwise.

Value

scoreContinuous signature scores
riskBinary risk classification, 1 being high risk and 0 being low risk.
mappingMapping used if necessary.
probeIf mapping is performed, this matrix contains the correspondence between the gene list (aka signature) and gene expression data.

References

Bell D, Berchuck A, Birrer M et al. (2011) "Integrated genomic analyses of ovarian carcinoma", Nature, 474(7353):609--615

Examples

Run this code

## load the ovcTCGA signature
data(sigOvcTCGA)
## load NKI dataset
data(nkis)
colnames(annot.nkis)[is.element(colnames(annot.nkis), "EntrezGene.ID")] <- "entrezgene"
## compute relapse score
ovcTCGA.nkis <- ovcTCGA(data=data.nkis, annot=annot.nkis, gmap="entrezgene", do.mapping=TRUE)
table(ovcTCGA.nkis$risk)